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Details of Grant 

EPSRC Reference: EP/V006436/1
Title: Accurate modelling of wind turbine wake spreading through consideration of realistic turbulent entrainment: revolutionising wind farm optimisation
Principal Investigator: Buxton, Dr O
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Carl von Ossietzky University Oldenburg KBR Vestas
Department: Aeronautics
Organisation: Imperial College London
Scheme: EPSRC Fellowship
Starts: 01 July 2021 Ends: 30 June 2026 Value (£): 1,290,141
EPSRC Research Topic Classifications:
Aerodynamics Wind Power
EPSRC Industrial Sector Classifications:
Related Grants:
Panel History:
Panel DatePanel NameOutcome
28 Sep 2020 Engineering Fellowship Interview Panel 29 and 30 September 2020 Announced
05 Aug 2020 Engineering Prioritisation Panel Meeting 5 and 6 August 2020 Announced
Summary on Grant Application Form
Wind energy currently produces 18% of the UK's power but, in a drive towards a de-carbonised economy by 2050, this proportion must increase substantially over the next decade. The UK government has committed to increase offshore wind power capacity by 1-2 GW per year until 2030, reflecting the fact that the country contains some of the best locations for offshore wind in Europe. As the UK becomes more reliant upon wind energy, it is of increasing importance to improve both the efficiency and reliability of wind farms. Since wind turbines which lie in the wakes of upstream machines produce less power and experience higher fatigue loading than those upstream, there is scope to achieve this goal by improving our ability to predict the wakes generated by wind turbines and thereby design an optimally laid out wind farm given knowledge of the prevailing wind conditions. Our ability to optimise wind farms is currently hampered by an over-reliance on out-of-date empiricism. This proposal seeks to rectify this by developing physics-based modelling tools to better describe individual wind-turbine wakes as well as the interactions between interacting wakes within a wind farm. Offshore wind farms are particularly amenable to optimisation due to the stability of the prevailing wind conditions in comparison to onshore sites.

Optimal spacing of wind turbines revolves around several factors. These are the desire to produce as much power as possible from a given site whilst at the same time minimising maintenance costs in response to fatigue damage caused by turbines sitting in the highly unsteady, turbulent wake of an upstream machine. This requires confident prediction of the spreading of wind turbine wakes plus a methodology to estimate the fatigue lifetime of wind turbine components in response to their predicted inflow conditions. In addition, there is the problem of predicting the global blockage in which the wind farm as a whole has the effect of diverting the wind over/around the wind farm meaning that the true inflow wind speed to the farm is not the same as the prevailing wind. Specifically, we will:

1. Perform innovative experiments in order to better understand the flow physics underpinning the spreading of turbulent wakes. This will involve exploring the interactions in the near wake between the coherence introduced at multiple length scales simultaneously by, for example, the tower, nacelle and blade-tip vortices. In addition we will explore the physics behind the spreading of the produced wake due to the phenomenon of entrainment, which is the process by which mass/energy is transferred from the background into the wake. In particular we will focus on the effect of atmospheric, and wake, turbulence on entrainment.

2. Take this new physical understanding and translate it into a physics-based model for the spreading of an individual wind-turbine wake.

3. Devise a methodology to make accurate predictions for the fatigue lifetime of vulnerable wind-turbine components (e.g. the gear box/trailing edge bond etc.) in response to the fluctuating inflow caused by atmospheric/wake turbulence.

4. Produce a model to correct for the global blockage that an entire wind farm represents to the oncoming wind.

5. Finally, develop a low-cost, physics-based wind farm optimisation tool and disseminate it to the UK's wind-energy sector. The model will take as inputs the details of the turbines to be erected, the atmospheric conditions at the specified site and the agreed strike price/MWh to be paid for the generated power. The output will be the optimal number and layout of wind turbines for an efficient offshore wind farm. We have attracted three partners from across the wind-energy sector who will play a vital role in ensuring that the output of this research is disseminated to the key stakeholders in the UK in a form that can be implemented by the industry straight away.
Key Findings
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Organisation Website: http://www.imperial.ac.uk